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SPH

The smooth particle hydrodynamics (SPH) technique is a purely Lagrangian method. SPH discretizes a fluid in a series of interpolation points (SPH particles) whose distribution follows the mass density of the fluid and their evolution relies on a weighted interpolation over close neighboring particles.

SPH simulations represent computationally demanding calculations. Therefore, trade-offs are made between temporal and spatial scales, resolution, dimensionality (3-D or 2-D), and approximated versions of the physics involved. The parallelization of SPH codes is not trivial due to their boundless nature and the absence of a structured particle grid. SPHYNX, ChaNGa, and SPH-flow are the three SPH codes selected in the PASC SPH-EXA project proposal. The performance of these codes is negatively impacted by factors, such as multiple time-stepping and gravity. Therefore, the goal is to extrapolate their common basic SPH features, which are consolidated in a fully optimized, Exascale-ready, MPI+X, pure-SPH, mini-app.

SPH-EXA mini-app

SPH-EXA mini-app is a C++17 headers-only code with no external software dependencies. The parallelism is currently expressed via following models: MPI, OpenMP, OpenMP4.5 target offloading, OpenACC and CUDA.

Check our wiki for more details

Folder structure

SPH-EXA
├── README.md
├── docs
├── domain                            - cornerstone octree and domain
│   ├── include
│   │   └── cstone
│   │       ├── CMakeLists.txt
│   │       ├── cuda
│   │       ├── domain
│   │       ├── findneighbors.hpp
│   │       ├── halos
│   │       ├── primitives
│   │       ├── sfc
│   │       ├── tree
│   │       └── util
│   └── test                         - cornerstone unit- performance-
│       ├── integration_mpi            and integration tests
│       ├── performance
│       ├── unit
│       └── unit_cuda
├── include                          - folder containing all sph functions
│   └─── sph
│       ├── cuda
│       └─── kernel
├── scripts
├── src                              - folder containing test case main function
│   ├── evrard
│   ├── sedov
│   └── sqpatch
├── test
└── tools

Compile

Use the following commands to compile and run the SquarePatch example:

  • OpenMP: make omp
  • OpenMP + CUDA: make omp+cuda
  • MPI + OpenMP: make mpi+omp
  • MPI + OpenMP + OpenMP 4.5 Offloading: mpi+omp+target
  • MPI + OpenMP + CUDA: make mpi+omp+cuda
  • MPI + OpenMP + OpenACC: make mpi+omp+acc

Compiled binaries are placed in bin/ in the project root folder.

Run

To run the SPH-EXA type shell bin/{compiled_parallel_model}.app arguments

Possible arguments for the Square Patch test case:

  • -n NUM : Run the simulation with NUM^3 (NUM to the cube) number of particles
  • -s NUM : Run the simulation with NUM of iterations (time-steps)
  • -w NUM : Dump particle data every NUM iterations (time-steps)
  • --quiet : Don't print any output to stdout

Example usage:

  • ./bin/omp.app -n 100 -s 1000 -w 10 Runs the Square Patch simulation with 1 million particles for 1000 iterations (time-steps) with OpenMP and dumps particles data every 10 iterations
  • ./bin/omp+cuda.app -n 20 -s 500 Runs the Square Patch simulation with 8 thousands particles for 500 iterations (time-steps) with OpenMP and CUDA
  • mpirun bin/mpi+omp+cuda.app -n 500 -s 10 Runs the Square Patch simulation with 125 million particles for 10 iterations (time-steps) with MPI, OpenMP and CUDA
  • mpirun bin/mpi+omp+target.app -n 100 -s 10000 Runs the Square Patch simulation with 1 million particles for 10000 iterations (time-steps) with MPI, OpenMP and OpenMP4.5 target offloading

Authors (alphabetical order)

  • Ruben Cabezon**
  • Aurelien Cavelan**
  • Florina Ciorba**
  • Michal Grabarczyk**
  • Danilo Guerrera**
  • David Imbert**
  • Sebastian Keller**
  • Lucio Mayer**
  • Ali Mohammed**
  • Jg Piccinali**
  • Tom Quinn**
  • Darren Reed**

License

This project is licensed under the MIT License - see the LICENSE file for details

Acknowledgments

  • PASC SPH-EXA project

Packages

No packages published

Languages

  • C++ 85.2%
  • Cuda 9.2%
  • Shell 2.9%
  • Python 1.3%
  • CMake 1.1%
  • Makefile 0.3%